The Cognitive Load of Financing Constraints: Evidence from Large-Scale Wage Surveys

In this paper, we take advantage of the implicit cognitive exercise available in standard Labor Force Surveys in order to provide a new, population-wide quantification of the cognitive load associated with financial constraints (Mullainathan and Shafir, 2013). This quantification is based on a well-defined index of worker-level attention which filters out rounding behavior and reporting biases. We estimate it using unsupervised clustering techniques and find that workers perceive their own wages with a degree of uncertainty of around 10%, which through the lens of a simple rational signal extraction model translates into estimates of workers' attention ranging from 30% to 84% depending on their wage, education, tenure and gender. Most importantly, the attention of the lowest paid 30% of workers is cyclical and increases steadily (by 17 percentage points) in the ten days preceding payday, before immediately dropping on that day. We show theoretically that this pattern is indicative of end-of-month financing (liquidity) constraints. Furthermore, it reveals that these financing constraints induce cognitive costs arising from the not too concave (or convex) costs of achieving high levels of attention, and the convex costs of maintaining them over time. Our model identifies a lower bound for the annual attention cost burden incurred by financially constrained workers, which ranges between 10 and 50 euros depending on risk aversion.